Oscar Castillo

Towards Vision-Spatiotemporal Fusion in Traffic Forecasting: A Survey on Cross-Modal Alignment

Traffic forecasting is evolving, with world models emerging as a powerful framework applicable to tasks such as core state, trajectory, event, and demand forecasting. These tasks involve both visual and spatiotemporal data, yet most existing methods treat them separately, hindering a unified underst